Dynamic managerial capabilities: Scale development and validation

Studies on dynamic managerial capabilities still have a rather theoretical nature, and there is great difficulty in finding a valid, reliable instrument to measure this construct. The present study contributes to solving this problem: It aims to develop and validate a scale to measure dynamic managerial capabilities. In this investigation, we develop a scale for three factors related to dynamic managerial capabilities: human capital, managerial cognition (already described in the literature), and relationship networks. The prominent finding in this research is the factor that is referred to here as relationship networks.     

Exploring sources and outcomes of trust and commitment to nonprofit organizations: The case of Amnesty International Portugal

The interactions between customers and organizations have been regarded as a core aspect in cocreating and developing new products and practices. The current study explores these interactions in the context of citizens and nonprofit organizations. The study comprises two parts: (a) a qualitative approach using interviews and the analysis of social networks to better understand the organization's social media marketing practices and corresponding outcomes and (b) a quantitative approach to analyze antecedents and outcomes of trust and being committed to participate in a nonprofit organization such as Amnesty International. From the qualitative approach, the findings highlight that Amnesty International uses social media (Facebook) to share information, and citizens tend to consider sharing posts, but they do not express new ideas or interact with the organization. These findings contribute to structure the model analyzed in the second stage of the research. Regarding the qualitative approach, the results show that organizational credibility is the most significant driver of trust followed by communicative ability. Affectively commitment to participation and relationship perception act as outcomes of overall commitment.     

Statistical Decision Problems and Bayesian Nonparametric Methods

This paper considers parametric statistical decision problems conducted within a Bayesian nonparametric context. Our work was motivated by the realisation that typical parametric model selection procedures are essentially incoherent. We argue that one solution to this problem is to use a flexible enough model in the first place, a model that will not be checked no matter what data arrive. Ideally, one would use a nonparametric model to describe all the uncertainty about the density function generating the data. However, parametric models are the preferred choice for many statisticians, despite the incoherence involved in model checking, incoherence that is quite often ignored for pragmatic reasons. In this paper we show how coherent parametric inference can be carried out via decision theory and Bayesian nonparametrics. None of the ingredients discussed here are new, but our main point only becomes evident when one sees all priors—even parametric ones—as measures on sets of densities as opposed to measures on finite-dimensional parameter spaces.     

Flexible exchange rates as shock absorbers

In this paper we analyze empirically the effect of terms of trade shocks on economic performance under alternative exchange rate regimes. We are particularly interested in investigating whether terms of trade disturbances have a smaller effect on growth in countries with a flexible exchange rate arrangement. We also analyze whether negative and positive terms of trade shocks have asymmetric effects on growth, and whether the magnitude of these asymmetries depends on the exchange rate regime. We find evidence suggesting that terms of trade shocks get amplified in countries that have more rigid exchange rate regimes. We also find evidence of an asymmetric response to terms of trade shocks: the output response is larger for negative than for positive shocks. Finally, we find evidence supporting the view that, after controlling for other factors, countries with more flexible exchange rate regimes grow faster than countries with fixed exchange rates.     

A UNIFIED PRESENTATION OF COMPETITION ANALYSIS IN TWO-SIDED MARKETS

The goal of this paper is to present quantitative tools to manage competition policy analysis in two-sided platforms, based on a common framework for transaction and non-transaction platforms. We explore tools for relevant market definition [Critical Loss Analysis and a small but significant non-transitory increase in price (SSNIP) test], unilateral effects indicators [Upward Pricing Pressure (UPP) and Gross Upward Pricing Pressure Index (GUPPI)] and tests for exclusionary practices. We review dispersed results in the literature and fill the gaps where appropriate. We highlight the required changes from the usual one-sided market framework and tools. While discussions of antitrust tools can be found in specialized forums devoted to advances in competition policy analysis, we organize the material in an integrated framework.     

Asymmetry, realised volatility and stock return risk estimates

In this paper we estimate minimum capital risk requirements for short and long positions with three investment horizons, using the traditional GARCH model and two other GARCH-type models that incorporate the possibility of asymmetric responses of volatility to price changes. We also address the problem of the extremely high estimated persistence of the GARCH model to generate observed volatility patterns by including realised volatility as an explanatory variable into the model??s variance equation. The results suggest that the inclusion of realised volatility improves the GARCH forecastability as well as its ability to calculate accurate minimum capital risk requirements and makes it quite competitive when compared with asymmetric conditional heteroscedastic models such as the GJR and the EGARCH.